RT Journal Article SR Electronic T1 mebipred: identifying metal-binding potential in protein sequence JF bioRxiv FD Cold Spring Harbor Laboratory SP 2021.08.12.456141 DO 10.1101/2021.08.12.456141 A1 AA Aptekmann A1 J Buongiorno A1 D Giovannelli A1 M Glamoclija A1 DU Ferreiro A1 Y Bromberg YR 2021 UL http://biorxiv.org/content/early/2021/08/13/2021.08.12.456141.abstract AB Metal-binding proteins have a central role in maintaining life processes. Nearly one-third of known protein structures contain metal ions that are used for a variety of needs, such as catalysis, DNA/RNA binding, protein structure stability, etc. Identifying metal-binding proteins is thus crucial for understanding the mechanisms of cellular activity. However, experimental annotation of protein metal-binding potential is severely lacking, while computational techniques are often imprecise and of limited applicability.We developed a novel machine learning-based method, mebipred, for identifying metal-binding proteins from sequence-derived features. This method is nearly 90% accurate in recognizing proteins that bind metal ions and ion containing ligands. Moreover, the identity of ten ubiquitously present metal ions and ion-containing ligands can be annotated. mebipred is reference-free, i.e. no sequence alignments are involved, and outperforms other prediction methods, both in speed and accuracy. mebipred can also identify protein metal-binding capabilities from short sequence stretches and, thus, may be useful for the annotation of metagenomic samples metal requirements inferred from translated sequencing reads. We performed an analysis of microbiome data and found that ocean, hot spring sediments and soil microbiomes use a more diverse set of metals than human host-related ones. For human-hosted microbiomes, physiological conditions explain the observed metal preferences. Similarly, subtle changes in ocean sample ion concentration affect the abundance of relevant metal-binding proteins. These results are highlight mebipred’s utility in analyzing microbiome metal requirements.mebipred is available as a web server at services.bromberglab.org/mebipred and as a standalone package at https://pypi.org/project/mymetal/Competing Interest StatementThe authors have declared no competing interest.mebipredMetal-binding predictorPDBProtein Data BankBLASTBasic local alignment search tool